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Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals
Name
s42003-021-02325-5.pdf
Description
Published version
Size
2.51 MB
Format
Adobe PDF
Checksum (MD5)
3577fbd11f8ff99fd1b477db5adfb588
Author(s)
Kiwimagi, Katherine A
Letendre, Justin H
Weinberg, Benjamin H
Wang, Junmin
Chen, Mingzhe
Watanabe, Leandro
Myers, Chris J
Beal, Jacob
Wong, Wilson W
Weiss, Ron
Date Issued
December 2021
Journal
Communications Biology
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
AbstractMany synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals. Using a combination of signal-to-noise ratio (SNR), area under a receiver operating characteristic curve (AUC), and fold change (FC), we evaluate three small-molecule inducible digitizer designs demonstrating FC up to 508x and SNR up to 3.77 dB. To study their behavior further and improve modularity, we develop a mixed phenotypic/mechanistic model capable of predicting digitizer configurations that amplify a synNotch cell-to-cell communication signal (Δ SNR up to 2.8 dB). We hope the metrics and modeling approaches here will facilitate incorporation of these digitizers into other systems while providing an improved workflow for gene circuit characterization.
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
10.1038/s42003-021-02325-5
